EP1592008 discloses a method for mixing two digital data sets into a third digital data set. In order to fit two digital data sets into a single digital data set with a size smaller than the sum of the sizes of the two digital data sets, a reduction of information in the two digital data sets is required. EP1592008 achieves this reduction in defining an interpolation at samples between a first set of predefined positions in the first digital data set and at a non-coinciding set of samples between predefined positions in the second digital data set. The value of the samples between the predefined positions of the digital data sets are adjusted to the interpolation value. After performing this reduction in information in the two digital data sets, each sample of the first digital data set is summed with the corresponding sample of the second digital data set. This results in a third digital data set comprising the summed samples. This summation of samples together with known relationship of the offset between the predefined positions between the first digital data set and the second digital data set allows the recovery of the first digital data set and the second digital data set, albeit only with the samples adjusted by interpolation between the predefined positions. When the method of EP1592008 is used for audio streams this interpolation is not noticeable and the third digital data set can be played as a mixed representation of the two digital data sets comprised. In order to enable the retrieval of the first and second digital data set with the adjusted samples, a start value for both the first and second digital data set must be known and hence these two values are also stored during mixing to allow a later unraveling of the two digital data sets from the third digital data set.
EP2092791 discloses an other method for mixing two digital data sets into a third digital data set. In EP2092791, instead of using interpolation, sample values are adjusted by equating them to the sample value of a neighbouring sample. A disadvantage of this method is that it introduces errors which have to be corrected during decoding.
Both methods, the interpolation in EP1592008 and the equating in EP2092791, effectively adjust the sample value of a subset of samples, thus introducing an error. In order to be able to correct this error during decoding for each adjusted sample the error must be stored for later retrieval during decoding. As storing all errors would result in large files, EP2092791 discloses a method wherein, after determining the errors, a reduction is performed by grouping the errors into error groups. For each error group a representative approximated error is chosen resulting in a sets of error approximations. These sets of error approximations are indexed. For each sample affected by the adjustment an index is chosen corresponding to that error approximation which is closest to the error or satisfies other criteria such as compensation for errors occurring when reversing the interpolation because multiple adjusted sample values are used during the reversing of the interpolation.
It is however still a disadvantage of EP 2092791 that the amount of data which needs to be stored for the sets of error approximations is still large.
It is an objective of the present invention to further reduce the amount of data to be stored for later retrieval during decoding.